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In each case, we examined the use of tree statistics as features for prediction methods in comparison with prediction from features derivable solely from raw cell counts.
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In this paper, first results from synchrotron X-ray diffraction and tomography experiments performed on ID11 and ID19 (respectively) at the ESRF, Grenoble, are presented and discussed in comparison with predictions from finite element modeling.
Effectiveness of the proposed model is carried out to real-world engineering test case in comparison with other prediction models.
The results of this study showed the superior performance of neural network models in comparison with the prediction models obtained by linear and nonlinear regressions, particularly when testing evaluations were chosen from the boundaries of mixture proportions.
In this paper, we show that the pattern-based approach improves the efficiency of the solution in comparison with traditional prediction approaches, e.g., based on collaborative filtering.
Experimental results indicate that the proposed monocular method can raise compression ratio 3.6 to 7.5 times, speed up compression time 5.3 to 22.3 times, and improve the image quality 3.81 to 9.24 dB in comparison with circular prediction mapping and non-contractive interframe mapping.
For the flames investigated, the observed differences in the concentration profiles of some potential precursors of benzene are discussed in comparison with the predictions of flame modeling.
The constitutional defects on both sides of stoichiometry for these systems were found to be of the anti-site type in comparison with model predictions.
Second, for γ > γc, feedback compensation was reduced up to 21%, in comparison with the predictions of LST.
In Fig. 7, the measured values are shown in comparison with the predictions obtained from CFD simulations.
The supplement gives detailed insight into the compounds we used for testing and the results of the screening, in comparison with the predictions [see Additional file 4].
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